2019
DOI: 10.1007/s40430-019-1774-z
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Monitoring of microturning process using acoustic emission signals

Abstract: The great challenge of modern industry is to carry out an online prediction in the shop floor during the machining to define the exact tool breakage instant and simultaneously improve the quality of manufactured products. Acoustic emission sensors have been used to monitoring traditional and non-traditional machining processes. This work shows a study of the online monitoring in the microturning process using an acoustic emission sensor. A factorial design was performed to examine the effect of the feed rate, … Show more

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Cited by 8 publications
(3 citation statements)
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References 19 publications
(17 reference statements)
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“…9. Taking an experimental result as an example, the coordinates of the leakage hole is (0,0) and the coordinates of the sensor array (element 1) is (30, -45), and the angle-energy relationship can be calculated according to (5)(6)(7)(8)(9)(10)(11). For the visual representation, the relationship is plotted as shown in Fig.…”
Section: Figure 17 Locating Error Distribution Chartmentioning
confidence: 99%
See 1 more Smart Citation
“…9. Taking an experimental result as an example, the coordinates of the leakage hole is (0,0) and the coordinates of the sensor array (element 1) is (30, -45), and the angle-energy relationship can be calculated according to (5)(6)(7)(8)(9)(10)(11). For the visual representation, the relationship is plotted as shown in Fig.…”
Section: Figure 17 Locating Error Distribution Chartmentioning
confidence: 99%
“…In consequence, it is not suitable for leak detection in large vessels such as spacecraft, and has poor localization accuracy due to the introduction of manual labor. In addition, another method that detects and locates the source of the leakage using the acoustic emission signal excited when the leak is generated, such as the UltraWIS system [5], which is also been applied to pipeline gas leak detection successfully [6,7], structural health monitoring [8], pressure vessel leakage locating [9] and other fields. Each method has high locating accuracy, good real-time performance, and a relatively simple system.…”
mentioning
confidence: 99%
“…Several experiments were carried out and the data thus obtained is used for the training and testing of an artificial neural network. Ribeiro Filho et al [29] used an acoustic emission sensor for online monitoring of the micro turning process. Babu et al [30] presented the usage of copper nanofluids with minimum quantity lubrication (MQL) in turning on EN24 steel.…”
Section: Introductionmentioning
confidence: 99%